What Are Common Qiskit Commands?

Programming a Quantum Computer

import qiskit
import random
import matplotlib.pyplot as plt
from sklearn.metrics import precision_score
from sklearn.metrics import recall_score
from sklearn.metrics import confusion_matrix
from functools import reduce
from math import sqrt, pi, cos, sin, exp, asin, ceil
from qiskit import QuantumCircuit, ClassicalRegister, QuantumRegister
from qiskit import execute, Aer
from qiskit.visualization import plot_histogram, plot_bloch_multivector, plot_state_qsphere

.cry(theta, control_qubit, target_qubit)
.cx(control_qubit, target_qubit)
.ccx(control_qubit1, control_qubit2, target_qubit)
.draw('text') / .draw('mpl') /
.get_backend('statevector_simulator')
- aer_simulator, aer_simulator_statevector, aer_simulator_density_matrix, aer_simulator_stabilizer, aer_simulator_matrix_product_state, aer_simulator_extended_stabilizer, aer_simulator_unitary, aer_simulator_superop
  qasm_simulator, statevector_simulator, unitary_simulator, pulse_simulator
.get_counts(): returns a dictionary that has the counts for each qubit
.get_unitary()
.h(qubit) / .h([0, 1, 2, 3])
.initialize()
.measure_all() / .measure(qr[1], cr[1])
.result()
.ry(theta, qubit):
.x(0)